Memory Bounds for the Distributed Execution of a Hierarchical Synchronous Data-Flow Graph

Abstract : This paper presents an application analysis technique to define the boundary of shared memory requirements of Multiprocessor System-on-Chip (MPSoC) in early stages of development. This technique is part of a rapid prototyping process and is based on the analysis of a hierarchical Synchronous Data-Flow (SDF) graph description of the system application. The analysis does not require any knowledge of the system architecture, the mapping or the scheduling of the system application tasks. The initial step of the method consists of applying a set of transformations to the SDF graph so as to reveal its memory characteristics. These transformations produce a weighted graph that represents the different memory objects of the application as well as the memory allocation constraints due to their relationships. The memory boundaries are then derived from this weighted graph using analogous graph theory problems, in particular the Maximum-Weight Clique (MWC) problem. Stateof-the-art algorithms to solve these problems are presented and a heuristic approach is proposed to provide a near-optimal solution of the MWC problem. A performance evaluation of the heuristic approach is presented, and is based on hierarchical SDF graphs of realistic applications. This evaluation shows the efficiency of proposed heuristic approach in finding near optimal solutions.
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Karol Desnos, Maxime Pelcat, Jean François Nezan, Slaheddine Aridhi. Memory Bounds for the Distributed Execution of a Hierarchical Synchronous Data-Flow Graph. 12th International Conference on Embedded Computer Systems: Architecture, Modeling and Simulation (SAMOS XII), Jul 2012, Agios Konstantinos, Greece. pp.160. ⟨hal-00721335⟩

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